Biometric identification systems play an important role in the field of user identification. For example, finger print scanners, iris scanners and face recognition systems are typically used for user identification. Such biometric identification systems require a direct interaction with persons to be identified. E.g. the persons have to come into direct contact with a scanner, e.g. finger print scanners, or have to look at least towards the direction of a camera system, e.g. for face recognition or iris scanning. These requirements are uncomfortable and, if a large group of persons shall be identified at the same time, further time-consuming.
Furthermore, the mentioned biometric identification systems are often based on skin detection. Usually, skin detection systems acquire RGB images, analyse the colour space and deliver a map identifying skin-coloured regions and other regions. These skin detection systems work fine until an image with skin-coloured regions is presented to them. In this case the skin-coloured regions of the image which represent “fake” skin are detected as “real” human skin. Therefore, the mentioned biometric identification systems are cheatable. For example, a finger print system can be cheated by a simple paper copy of a finger print. In the same way also iris scan systems or face recognition systems can be bypassed by using images of irises or a face.
Although there exist techniques for biometric user identification and for human skin detection, it is generally desirable to provide an image processing method and an image processing system for reliable user identification and/or for reliable skin detection.